In silico analysis and developmental expression of ubiquitin-conjugating enzymes in Schistosoma mansoni

2015 ◽  
Vol 114 (5) ◽  
pp. 1769-1777 ◽  
Author(s):  
Marcela P. Costa ◽  
Victor F. Oliveira ◽  
Roberta V. Pereira ◽  
Fabiano C. P. de Abreu ◽  
Liana K. Jannotti-Passos ◽  
...  
Keyword(s):  
Schistosoma Mansoni ◽  
In Silico ◽  
In Silico Analysis ◽  
Developmental Expression ◽  
Conjugating Enzymes ◽  
Ubiquitin Conjugating Enzymes ◽  
Silico Analysis

scholarly journals Comprehensive In Silico Analysis and Transcriptional Profiles Highlight the Importance of Mitochondrial Dicarboxylate Carriers (DICs) on Hypoxia Response in Both Arabidopsis thaliana and Eucalyptus grandis

Plants ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 181
Author(s):  
Pedro Barreto ◽  
Mariana L. C. Arcuri ◽  
Rômulo Pedro Macêdo Lima ◽  
Celso Luis Marino ◽  
Ivan G. Maia
Keyword(s):  
In Silico ◽  
Seedling Survival ◽  
Expression Patterns ◽  
Eucalyptus Grandis ◽  
In Silico Analysis ◽  
Developmental Expression ◽  
Hypoxia Response ◽  
Submergence Stress ◽  
Wide Range ◽  
Silico Analysis

Plant dicarboxylate carriers (DICs) transport a wide range of dicarboxylates across the mitochondrial inner membrane. The Arabidopsis thalianaDIC family is composed of three genes (AtDIC1, 2 and 3), whereas two genes (EgDIC1 and EgDIC2) have been retrieved in Eucalyptus grandis. Here, by combining in silico and in planta analyses, we provide evidence that DICs are partially redundant, important in plant adaptation to environmental stresses and part of a low-oxygen response in both species. AtDIC1 and AtDIC2 are present in most plant species and have very similar gene structure, developmental expression patterns and absolute expression across natural Arabidopsis accessions. In contrast, AtDIC3 seems to be an early genome acquisition found in Brassicaceae and shows relatively low (or no) expression across these accessions. In silico analysis revealed that both AtDICs and EgDICs are highly responsive to stresses, especially to cold and submergence, while their promoters are enriched for stress-responsive transcription factors binding sites. The expression of AtDIC1 and AtDIC2 is highly correlated across natural accessions and in response to stresses, while no correlation was found for AtDIC3. Gene ontology enrichment analysis suggests a role for AtDIC1 and AtDIC2 in response to hypoxia, and for AtDIC3 in phosphate starvation. Accordingly, the investigated genes are induced by submergence stress in A. thaliana and E. grandis while AtDIC2 overexpression improved seedling survival to submergence. Interestingly, the induction of AtDIC1 and AtDIC2 is abrogated in the erfVII mutant that is devoid of plant oxygen sensing, suggesting that these genes are part of a conserved hypoxia response in Arabidopsis.

scholarly journals In vitro and in silico analysis of signal peptides from the human blood fluke,Schistosoma mansoni

2005 ◽  
Vol 45 (2) ◽  
pp. 201-211 ◽  
Author(s):  
Mark S. Pearson ◽  
Donald P. McManus ◽  
Danielle J. Smyth ◽  
Fred A. Lewis ◽  
Alex Loukas
Keyword(s):  
Schistosoma Mansoni ◽  
Human Blood ◽  
In Silico ◽  
In Silico Analysis ◽  
Signal Peptides ◽  
Blood Fluke ◽  
Silico Analysis

Schistosoma mansoni histones: From transcription to chromatin regulation; an in silico analysis

2012 ◽  
Vol 183 (2) ◽  
pp. 105-114 ◽  
Author(s):  
Letícia Anderson ◽  
Raymond J. Pierce ◽  
Sergio Verjovski-Almeida
Keyword(s):  
Schistosoma Mansoni ◽  
In Silico ◽  
In Silico Analysis ◽  
Chromatin Regulation ◽  
Silico Analysis

In silico analysis of ubiquitin/ubiquitin-like modifiers and their conjugating enzymes in Entamoeba species

2012 ◽  
Vol 111 (1) ◽  
pp. 37-51 ◽  
Author(s):  
Shweta Arya ◽  
Gaurav Sharma ◽  
Preeti Gupta ◽  
Swati Tiwari
Keyword(s):  
In Silico ◽  
In Silico Analysis ◽  
Conjugating Enzymes ◽  
Silico Analysis

A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

2020 ◽  
Vol 47 (6) ◽  
pp. 398-408
Author(s):  
Sonam Tulsyan ◽  
Showket Hussain ◽  
Balraj Mittal ◽  
Sundeep Singh Saluja ◽  
Pranay Tanwar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Gallbladder Carcinoma ◽  
In Silico ◽  
In Silico Analysis ◽  
Transcriptomic Profile ◽  
Silico Analysis

In Silico Analysis of Single Nucleotide Polymorphism in Human Prothrombin Gene

2019 ◽  
Author(s):  
I. Farah ◽  
A. El-Mubark ◽  
M. Osman ◽  
A. Soliman ◽  
F. Ali ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
In Silico ◽  
In Silico Analysis ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Prothrombin Gene ◽  
Silico Analysis

Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki
Keyword(s):  
Data Analysis ◽  
Virtual Screening ◽  
In Silico ◽  
Model Development ◽  
In Silico Analysis ◽  
Material Design ◽  
Efficient Solutions ◽  
Biological Data ◽  
Cost Efficient ◽  
Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

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